2006 TEXAQS/GoMACCS 

Comprehensive Meteorological Analysis of TexAQS II data 

Combining Climate Change and Air Quality Research 

August 2007 

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Longitude

26

28

30

32

34

36Latitude

Boundary-layer profilers

Serial rawinsondes

Full tropospheric profilers

Boundary-layer profilers

NWS Rawinsondes

NEXRAD

Existing Upper-air Network

TexAQS-II Enhancements
Introduction 

NOAA ESRL has undertaken a comprehensive analysis of meteorological data collected during 

the TexAQS II experiment. This report describes the results of that analysis to date. The report 

is organized according to the questions presented by TCEQ. 

Initial findings were presented at the TEXAQS II / GoMACCS Data Analysis Workshop that 

was held in Austin on May 29 – June 1, 2007. Subsequent analysis has added to our 

understanding. The findings are presented here in the form of brief summaries. We also discuss 

planned further analysis. 

Data from many sources has been used in the following analyses. Most prominent among these 

are the rawinsondes launched from the NOAA Research Vessel Ronald H. Brown, the radar 

wind profilers deployed by TCEQ and NOAA, the High Resolution Doppler Lidar on Brown, 

and the TOPAZ airborne lidar. 

I. Data review and conceptual model 

Background: 

Nielsen-Gammon (2005) and Banta et al. (2005) have presented conceptual models for the 

highest ozone events in the Houston area. These emphasize the role of the coastal oscillation 

(bay breeze and sea breeze) in producing periods of very low wind speeds, which allow air 

parcels to accumulate emissions for a long time or multiple periods of time. These models 

remain valid for those events. However, it has been known since the TexAQS 2000 experiment 

that very low winds are not necessary for concentrations of ozone exceeding regulatory standards 

to be formed in the Houston area. Analysis of TexAQS II data has confirmed this. 

Results: 

The overall relationship between peak O3 concentrations and wind speed is shown in Fig. 1, 

which indicates the expected strong negative correlation between maximum in-network ozone 

enhancements above background and wind speed in the Houston area. Stronger winds produce 

greater dilution of the pollution emissions, and thus lower concentrations of pollutants. 

The blue points on Fig. 1 show the airborne-lidar-determined peak ozone concentrations vs. 10-

hr trajectory displacements, a surrogate for mean wind speed. Trajectories were calculated for 

heights in the middle of the boundary layer from the profiler network. The concentrations again 

decrease with increasing speed, but are everywhere larger than the surface measurements. 

Reasons for this trend include that the airborne data represent conditions aloft not subject to 

surface processes including removal, that the airborne lidar data represent averaging over shorter 

intervals, and that on days with stronger winds, plumes are narrower and harder to sample by 

fixed networks and also high concentrations may be blown out of the surface network before 

being sampled. 
Figure 1: Houston ozone enhancement (peak ozone values in urban plume minus background 

values) plotted vs. displacement of 10-hr trajectories, representing the vector-mean wind for the 

period, starting at Houston at 8:00 a.m. CST. Red symbols indicate data from surface 

measurement network (1-hr average), and blue symbols indicate data from airborne ozone lidar. 

“Add on” represents peak ozone concentrations observed minus background concentrations. 

This last point was expected to be a greater source of discrepancy between airborne and groundnetwork sampling, because the aircraft samples the pollution plume wherever it is, even though 

the maximum values may be occurring beyond the surface measurement network before the 

photochemical reactions are complete. Indeed, individual days have been identified with large 

discrepancies. In the overall sampling scheme, however, Fig. 1 shows that light winds (small 10-

hr displacements) were associated with large O3 enhancements by the Houston area and stronger 

wind speeds were associated with smaller enhancements. However, several stronger-wind days 

have been identified when the total O3 concentrations (background plus add-on) exceeded the 1-

hr standard. These days, most often associated with high background values, are being studied 

further to determine all processes responsible for the high concentrations. 

Interpretation and conclusions: 

Light winds and the coastal oscillation contribute to the highest ozone levels in Houston, but 

emissions are sufficient to produce strong ozone plumes downwind even on days with moderate 

winds. See also RSST Question B report section B2. 

II. Other sources of data 

Satellite images were archived by Owen Cooper at 

http://www.esrl.noaa.gov/csd/metproducts/texaqs/ 

Jerome Brioude has created a satellite cloud product combining infrared and visible imagery at 

4-km resolution every daytime hour from the GOES geostationary satellites. A cloud mask for 

each hour is calculated by selecting the darkest pixels over a 30 day time period. Then, pixels 

having a brightness temperature higher than 17K compared to the darkest pixel are defined as 

cloudy pixels. The cloud-top temperature is retrieved from the cloud mask applied on the 

infrared imagery. Then, cloud top altitude is estimated by cross referencing the cloud-top 

temperature with temperature fields from the 3-hourly ECMWF analyses (0.36x0.36 horizontal 

resolution), linearly interpolated in space and time. This dataset has a high temporal resolution 
(one hour) and relatively high geographical resolution (4km) to be used to study processes such 

as the sea breeze, the evolution of the daytime boundary, as well as the diurnal variation of low, 

mid and high level cloud across the Gulf of Mexico. 

Real-time data from the radar wind profilers operated by NOAA ESRL PSD are available at 

http://www.etl.noaa.gov/et7/data/archive/UneditedNonActive. Quality-controlled data are 

available on request. 

Quality-controlled data and products including winds and mixing depth from the NOAA ESRL 

CSD profiler at Moody are available from Wayne Angevine (Wayne.M.Angevine@noaa.gov). 

III. Were lower maximum ozone concentrations observed during TexAQS II 

meteorologically driven? 

Background: 

Although concentrations observed by surface monitors were lower in 2006 than in 2000, it is 

unclear whether concentrations were lower in general. Preliminary analysis of the airborne 

ozone lidar data indicates that peak concentrations observed in 2006 approached values 

observed during the 2000 study. A comprehensive analysis will more precisely assess 

similarities and diffences between the two years. Wind patterns and mixing heights in the two 

years were also somewhat different, and the implications of this are also under analysis. 

Interpretation and conclusions: 

Further analysis is needed to determine whether there were significant differences in ozone 

concentrations between 2000 and 2006, and if so, whether those differences can be attributed to 

meteorology. 

IV. What was the role of the coastal oscillation in ozone and ozone precursor accumulation 

and advection? 

Background: 

The prevailing conceptual model for the highest ozone concentrations in Houston involves 

stagnant or recirculating winds which allow for prolonged or multiple exposure of an air mass to 

emissions. The winds stagnate or reverse because of land-water temperature contrasts producing 

phenomena called land, bay, gulf, or sea breezes. Because Houston is almost at the critical 30 

degree latitude, these circulations have different characteristics than at higher latitudes, 

particularly a larger horizontal scale. The irregular shape of the coastline adds complexity. 

These phenomena are lumped together under the general term "coastal oscillation." 

Results: 

As discussed above, we continue to think that the coastal oscillation is associated with the 

strongest ozone events. For example, on 1 September 2006, instruments on the Ron Brown 

detected ozone mixing ratios over 180 ppb in Galveston Bay (figure 2). The high ozone was 

measured while the winds at the ship were from the east. Analysis shows that the air traversed 

the ship channel, went out over the Bay, and returned on the recirculating flow. 

Interpretation and conclusions: 

The coastal oscillation concept is an important tool for understanding the highest ozone events in 

Houston. 
Figure 2: Ozone mixing ratio and wind direction from the ship on 1 September. 
V. What was the role of the heat island effect over city, and over industrial areas? 

Background: 

Urban areas become hotter during the day and remain hotter at night than surrounding rural 

areas. This may affect wind patterns and thus pollutant transport, for example by strengthening 

or distorting land – sea breeze patterns. It also affects biogenic VOC emissions, and may affect 

anthropogenic fugitive VOC emissions. 

Results: 

Both Dallas and Houston have comprehensive networks of surface meteorology and chemistry 

sensors. The similarities of the networks and lack of terrain in Dallas and Houston allow for the 

comparison of their urban heat islands (UHI). The Dallas UHI, unperturbed by thermal flows 

driven by the land/sea temperature difference, is a well-defined phenomenon over the summers 

of 2000-2006 (Fig. 3a). Including all weather conditions, the average nighttime Turban – Trural

temperature difference was between 1.5o and 2.0o C and the average daytime difference was ~ 

1.0o C. Analysis of Houston temperature data, however, revealed a different picture due to the 

bay and gulf breezes (Fig. 3b). While the Houston UHI was a distinct phenomenon, even when 

including all weather conditions, the bay or gulf breeze modified the Houston UHI by cooling 

the city. Average nighttime Turban – Trural temperature differences in Houston were between 

1.75o and 2.75o C. However, during the day, the rural areas to the north and west of the city were 

often warmer than the downtown area during afternoon hours as a result of the sea breeze. 

Averaging the Houston Turban – Trural temperature differences over the summers of 2000-2006 

indicated a very small urban-rural temperature difference between 1400 to 1600 LST. In some 

individual years, such as 2000, 2003, 2005 and 2006, the urban areas were actually cooler than 

the rural areas, on average, in the mid-afternoon. These years had more bay breeze/gulf breeze 

activity to cool the urban area. 

Figure 3: Turban – Trural for each of the 7 summers analyzed, and the average for all summers. 

“Summer” includes all days from June 1 – September 30. a) Dallas. b) Houston. 

Interpretation and conclusions: 

Houston has a distinct urban heat island signature, but it is different from the more classical 

situation exemplified by Dallas because of the coastal oscillation. Implications of this for ozone 

and aerosol transport, as distinct from the coastal oscillation winds, remain to be explored. 
VI. What was the role of low mixing depths over Galveston Bay? 

Background: 

Mixing depth is a first-order control on pollutant concentrations, defining the vertical dimension 

of the volume through which emissions and products are diluted. Mixing depths over Galveston 

Bay have been thought to be generally lower than over surrounding land at midday (and 

probably higher at night), but measurements have been scarce. 

Results: 

The lidars on Brown, and rawinsondes launched from the ship, provide much improved 

measurements of mixing depths over the Bay during the 2006 study. In addition, surface heat, 

momentum, and moisture fluxes were measured on the ship, providing information about the 

local forcing contributing to the mixing depth. Figure 4 shows mixing depths determined from 

the lidar measurements for the Gulf, Bay, and areas surrounded by land. Average mixing depths 

over the Gulf showed little diurnal cycle. Over the Bay, there was some sign of diurnal 

variation, an unknown fraction of which is due to measuring air that has recently been influenced 

by land. However, the land influence is clearly less than at the locations surrounded by land. 

We can conclude that mixing depths over the Bay are generally lower than over land. Heat flux 

at the surface (figure 5) supports this, having values that are generally small but positive. As a 

specific example, figure 6 shows a sounding from the ship near the time of the peak ozone 

measurement on 1 September. The sounding location was in the Bay (figure 2) and the lowest 

layer wind was from the East, so the air in that layer had been over the bay for some time. A 

single mixing depth is difficult to define from this sounding, since there are multiple weakly 

defined layers, but the mixing depth is definitely below 400 m. 

Figure 4: Average mixing depths from the HRDL lidar measurements for locations in the Gulf, 

Bay, and surrounded by land. 

Interpretation and conclusions: 
We now have good evidence that mixing depths over the Bay during the day are lower than over 

the surrounding land. In the ideal scenario of highest ozone formation, air passes over the ship 

channel area, picking up large concentrations of precursor emissions, and then stagnates over the 

Bay while photochemistry proceeds. Moderate mixing depth over the Bay keeps the 

concentrations relatively strong by limiting vertical dilution. This is the scenario that produced 

the strong ozone measured at the ship on 1 September 2006, as well as at surface monitors. 

When the continuing coastal oscillation moves this air back over the urban area, it picks up more 

emissions. Depending on the time of day, it may also be mixed to greater depth as it moves 

inland. Thus the influence of the lower mixing depth over the Bay may be limited to areas 

relatively near shore. It should also be noted that there were days when the lower mixed layer 

over the Bay was cleaner than air in the lower layer in surrounding areas. 

Figure 5: All 10-minute heat flux measurements from the ship when it was in Galveston Bay, 

plotted versus time of day (left) and wind direction (right). 
Figure 6: Rawinsonde sounding from Brown launched in the Bay at 1752 UTC 1 September. 

VII. What was the relationship between mixing depth and land cover? 

Background: 

We generally expect that land use or land cover types that are wetter will lead to lower mixing 

depths than drier areas. Climatologies and vegetation indicate moister conditions to the east of 

Houston and nearer to the coast, and more arid conditions to the west and inland. However, 

there are many complicating factors, including antecedent rainfall and current cloud cover. This 

question is also related to the urban height island (section V). 

Results: 

Mixing depth and aerosol layer depth measurements from wind profilers and airborne lidar give 

a general picture of the regional distribution of mixing depth. Airborne lidar flights revealed a 

significantly deeper mixed layer over the arid regions to the west, which is consistent with 

mixing-depth data from the profiler array, which indicated increases in peak afternoon mixing 

depths with distance from the coast. For example, figure 7 shows the statistical distributions of 

midday mixing depth from wind profilers at Moody and LaPorte. The distribution at Moody is 
sharply peaked near 1.5 km, while LaPorte has many lower heights and a broader distribution. 

Some of this variation is due to the coastal oscillation. 

Figure 7: Distribution of boundary layer heights (mixing heights) for Moody (upper) and 

LaPorte (lower) between 1 August and 15 September 2006. 

The airborne lidar data are being analyzed, and will provide a regional picture of mixing height 

on flight days. An example is shown in figure 8 for 16 August 2006. It shows the expected 

pattern of higher mixing heights to the northwest and lower heights near the coast. 
Figure 8: Mixed layer height (aerosol layer height) from the TOPAZ airborne lidar on 16 

August 2006. 

Interpretation and conclusions: 

There are definite patterns of differing mixing height in the region, but they are not simply 

attributable to differences in land cover. Future analyses and modeling studies should shed more 

light on this question. 

VIII. Trajectories 

Background: 

Trajectories are a commonly used tool to study the sources of polluted air masses. There are 

significant uncertainties associated with any calculated trajectory. A particle dispersion model 

provides a better picture of the uncertainties. We recommend that all available sources be 

consulted when attempting to analyze a particular case. 
Results: 

Trajectories may be created from wind profiler observations at 

http://www.etl.noaa.gov/programs/2006/texaqs/traj. An example is shown in figure 9. 

Figure 9: Trajectory plot from the wind profiler trajectory tool for 1 September 2006. Twelvehour backward trajectories at four height bands are shown. 

Particle dispersion model results for the TexAQS II mobile platforms are available at 

http://zardoz.nilu.no/~andreas/TEXAQS (these are a product of Andreas Stohl). Custom plots 

can be made interactively at 

http:/www.esrl.noaa.gov/csd/metproducts/flexpart/flexpart_interactive/flexpart_custom.html. 

An example is shown in figure 10. 
Figure 10: North American anthropogenic CO in the column for 1800 UTC 1 September 2006, 

calculated from the Flexpart model with GFS meteorology. 

IX. What was the role of meteorology in so-called transient high ozone events? 

Background: 

Rapid increases of ozone at surface monitoring sites have been termed "transient high ozone 

events." There has been some suspicion that these events were due to unknown or unusual 

chemistry. 

Results: 

Airborne mapping of ozone plumes shows that, near the sources, plumes can be rather sharpedged. Shifts in wind direction due to the coastal oscillation or larger-scale dynamics can advect 

these plumes over a monitor, leading to rapid increases in ozone at that site. 
Interpretation and conclusions: 

Meteorology is a sufficient explanation for so-called transient high ozone events.